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December 14, 2016, at 12:02 PM by 128.93.176.59 -
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||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|http://www-sop.inria.fr/members/Alexis.Joly/smartflore.png]]  ||'''Smart'Flore [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|android]] app''' for the discovery of the surrounding vegetal biodiversity. It includes three main features: (i) the geo-based exploration of the world’s largest repository of biodiversity occurrences (GBIF), (ii) the exploration of virtual botanical trails (created offline through a dedicated web application hosted by TelaBotanica NGO) and (iii) the access to a variety of information about the plants. Nowadays, it has been downloaded by more than 22K users. This work is part of the Floris'Tic project, supported by the "Programme Investissement d'Avenir" and involving teams of Agropolis Fondation, Tela Botanica, Inria, Cirad, Cnrs, Inra, Ird, UM.
to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/smartflore.png]]  ||'''Smart'Flore [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore&hl=en|android]] app''' for the discovery of the surrounding vegetal biodiversity. It includes three main features: (i) the geo-based exploration of the world’s largest repository of biodiversity occurrences (GBIF), (ii) the exploration of virtual botanical trails (created offline through a dedicated web application hosted by TelaBotanica NGO) and (iii) the access to a variety of information about the plants. Nowadays, it has been downloaded by more than 22K users. This work is part of the Floris'Tic project, supported by the "Programme Investissement d'Avenir" and involving teams of Agropolis Fondation, Tela Botanica, Inria, Cirad, Cnrs, Inra, Ird, UM.
December 14, 2016, at 12:02 PM by 128.93.176.59 -
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||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|http://www-sop.inria.fr/members/Alexis.Joly/smartflore.png]]  ||'''Smart'Flore [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|android]] app''' for the discovery of the surrounding vegetal biodiversity. It includes three main features: (i) the geo-based exploration of the world’s largest repository of biodiversity occurrences (GBIF), (ii) the exploration of virtual botanical trails (created offline through a dedicated web application hosted by TelaBotanica NGO) and (iii) the access to a variety of information about the plants. Nowadays, it has been downloaded by more than 22K users.
This work is part of the Floris'Tic project, supported by the "Programme Investissement d'Avenir" and involving teams of Agropolis Fondation, Tela Botanica, Inria, Cirad, Cnrs, Inra, Ird, UM.
to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|http://www-sop.inria.fr/members/Alexis.Joly/smartflore.png]]  ||'''Smart'Flore [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|android]] app''' for the discovery of the surrounding vegetal biodiversity. It includes three main features: (i) the geo-based exploration of the world’s largest repository of biodiversity occurrences (GBIF), (ii) the exploration of virtual botanical trails (created offline through a dedicated web application hosted by TelaBotanica NGO) and (iii) the access to a variety of information about the plants. Nowadays, it has been downloaded by more than 22K users. This work is part of the Floris'Tic project, supported by the "Programme Investissement d'Avenir" and involving teams of Agropolis Fondation, Tela Botanica, Inria, Cirad, Cnrs, Inra, Ird, UM.
December 14, 2016, at 12:01 PM by 128.93.176.59 -
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||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]]''': a gamified application dedicated to the crowdsourced identification of plants. Its objective is two folds: (i) train people to identify plants and (ii), validate/correct noisy plant observations. The software relies on several innovations related to the active training of the users, the tasks assignment and the Bayesian inference in the presence of highly partial knowledge. The software as well as the underlying new techniques have been entirely developed by  [[http://www.lirmm.fr/~servajean/|Maximilien Servajean]], a post-doc that I am currently supervising jointly with Dennis Shasha (New-York univ.). 
to:
||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]]''': a gamified application dedicated to the crowdsourced identification of plants (more than 25K users). Its objective is two folds: (i) train people to identify plants and (ii), validate/correct noisy plant observations. The software relies on several innovations related to the active training of the users, the tasks assignment and the Bayesian inference in the presence of highly partial knowledge. The software as well as the underlying new techniques have been entirely developed by  [[http://www.lirmm.fr/~servajean/|Maximilien Servajean]], a post-doc that I supervised jointly with Dennis Shasha (New-York univ.). 
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||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|http://www-sop.inria.fr/members/Alexis.Joly/smartflore.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|http://www-sop.inria.fr/members/Alexis.Joly/smartflore.png]]  ||'''Smart'Flore [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|android]] app''' for the discovery of the surrounding vegetal biodiversity. It includes three main features: (i) the geo-based exploration of the world’s largest repository of biodiversity occurrences (GBIF), (ii) the exploration of virtual botanical trails (created offline through a dedicated web application hosted by TelaBotanica NGO) and (iii) the access to a variety of information about the plants. Nowadays, it has been downloaded by more than 22K users.
This work is part of the Floris'Tic project, supported by the "Programme Investissement d'Avenir" and involving teams of Agropolis Fondation, Tela Botanica, Inria, Cirad, Cnrs, Inra, Ird, UM
.
December 14, 2016, at 11:55 AM by 128.93.176.59 -
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||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSUVNofuAMWUsHzKBSIQ1fVu2WQpTUNBQ1hsWsxTCUFWXivlTJC]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|http://www-sop.inria.fr/members/Alexis.Joly/smartflore.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
December 14, 2016, at 11:51 AM by 193.49.108.68 -
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||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|https://lh3.googleusercontent.com/aE6eUskWcDNlH4qgmMdf96sjiLM0JdT1_C2FJQ7Lfpjhy3anTAUoGXyw9qxLbXhYAtFc=w300-rw]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSUVNofuAMWUsHzKBSIQ1fVu2WQpTUNBQ1hsWsxTCUFWXivlTJC]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
December 14, 2016, at 11:49 AM by 193.49.108.68 -
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|| border=0
||%width=120% [[https://play.google.com/store/apps/details?id=org.flore.smart.smartflore|https://lh3.googleusercontent.com/aE6eUskWcDNlH4qgmMdf96sjiLM0JdT1_C2FJQ7Lfpjhy3anTAUoGXyw9qxLbXhYAtFc=w300-rw]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
December 14, 2016, at 11:48 AM by 193.49.108.68 -
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[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. It is developed by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and [[http://www.tela-botanica.org/|Tela Botanica]] NGO with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end of the platform has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. The platform generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. Pl@ntNet is on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. It is developed by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and [[http://www.tela-botanica.org/|Tela Botanica]] NGO with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end of the platform has been downloaded by more than 3M persons in 170 countries, which makes it the Inria software with the largest audience. The platform generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. Pl@ntNet is on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
February 10, 2016, at 10:47 AM by 128.93.176.77 -
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! Softwares
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! Other softwares
February 10, 2016, at 10:44 AM by 128.93.176.77 -
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||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]]''': a gamified application dedicated to the crowdsourced identification of plants. Its objective is two folds: (i) train people to identify plants and (ii), validate/correct noisy plant observations. The software relies on several innovations related to the active training of the users, the tasks assignment and the Bayesian inference in the presence of highly partial knowledge. The software as well as the underlying new techniques have been entirely developed by  [[http://www.lirmm.fr/~servajean/|Maximilien Servajean]], a post-doc that I am currently supervising jointly with Denis Shasha from New-York university
to:
||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]]''': a gamified application dedicated to the crowdsourced identification of plants. Its objective is two folds: (i) train people to identify plants and (ii), validate/correct noisy plant observations. The software relies on several innovations related to the active training of the users, the tasks assignment and the Bayesian inference in the presence of highly partial knowledge. The software as well as the underlying new techniques have been entirely developed by  [[http://www.lirmm.fr/~servajean/|Maximilien Servajean]], a post-doc that I am currently supervising jointly with Dennis Shasha (New-York univ.)
February 10, 2016, at 10:43 AM by 128.93.176.77 -
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||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]]''': a gamified application dedicated to the crowdsourced identification of plant images. Its objective is two folds: (i) training people to identify plants and (ii) validating/correcting noisy plant observations (in particular the ones produced through the Pl@ntNet mobile apps). The software includes several innovations related to the active training of the users, the tasks assignment and the Bayesian inference in the presence of highly partial knowledge. The software as well as the underlying new techniques have been entirely developed by  [[http://www.lirmm.fr/~servajean/|Maximilien Servajean]], a post-doc that I am currently supervising jointly with Denis Shasha from New-York university. 
to:
||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]]''': a gamified application dedicated to the crowdsourced identification of plants. Its objective is two folds: (i) train people to identify plants and (ii), validate/correct noisy plant observations. The software relies on several innovations related to the active training of the users, the tasks assignment and the Bayesian inference in the presence of highly partial knowledge. The software as well as the underlying new techniques have been entirely developed by  [[http://www.lirmm.fr/~servajean/|Maximilien Servajean]], a post-doc that I am currently supervising jointly with Denis Shasha from New-York university. 
February 10, 2016, at 10:41 AM by 128.93.176.77 -
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||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]]''': a gamified application dedicated to the crowdsourced identification of plant images. Its objective is two folds: (i) training people to identify plants and (ii) validating/correcting noisy plant observations (in particular the ones produced through the Pl@ntNet mobile apps). The software includes several innovations related to the active training of the users, the tasks assignment and the Bayesian inference in the presence of highly partial knowledge. The software as well as the underlying new techniques have been entirely developed by  [[http://www.lirmm.fr/~servajean/|Maximilien Servajean]], a post-doc that I am currently supervising jointly with Denis Shasha from New-York university.
February 10, 2016, at 10:29 AM by 128.93.176.77 -
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||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.jpg]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
February 10, 2016, at 10:29 AM by 128.93.176.77 -
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||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg.jpg]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg2.jpg]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
February 10, 2016, at 10:28 AM by 128.93.176.77 -
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||%width=120% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg.jpg]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=200% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg.jpg]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
February 10, 2016, at 10:28 AM by 128.93.176.77 -
Changed line 10 from:
||%width=120% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=120% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg.jpg]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
February 10, 2016, at 10:26 AM by 128.93.176.77 -
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||%width=120% [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=120% [[http://www.theplantgame.com/|http://www-sop.inria.fr/members/Alexis.Joly/tpg.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
February 10, 2016, at 10:22 AM by 193.49.108.68 -
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||%width=120% [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||''' [[www.theplantgame.com|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||''' [[http://www.theplantgame.com/|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
February 10, 2016, at 10:21 AM by 193.49.108.68 -
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[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. It is developed by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and [[http://www.tela-botanica.org/|Tela Botanica]] NGO with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end of the platform has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. The platform generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.  Pl@ntNet is on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]. 
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. It is developed by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and [[http://www.tela-botanica.org/|Tela Botanica]] NGO with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end of the platform has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. The platform generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. Pl@ntNet is on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
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||%width=120% [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH). ([[http://m.plantnet-project.org/ | Try the web version !]])

to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).

|| border=0
||%width=120% [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png
]]  ||''' [[www.theplantgame.com|The Plant Game]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through convolutional neural network technologies coupled with a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH).
February 10, 2016, at 10:14 AM by 193.49.108.68 -
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH). ([[http://m.plantnet-project.org/ | Try the web version !]])
to:
||%width=120% [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH). ([[http://m.plantnet-project.org/ | Try the web version !]])
February 10, 2016, at 10:13 AM by 193.49.108.68 -
Changed lines 4-5 from:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. The platform generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.  Pl@ntNet is on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. It is developed by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and [[http://www.tela-botanica.org/|Tela Botanica]] NGO with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end of the platform has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. The platform generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.  Pl@ntNet is on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
Changed line 7 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH). ([[http://m.plantnet-project.org/ | Try the web version !]])
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH). ([[http://m.plantnet-project.org/ | Try the web version !]])
February 10, 2016, at 10:11 AM by 193.49.108.68 -
Changed lines 4-5 from:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity ([[http://m.plantnet-project.org/ | Try the web version !]]).  Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. The platform generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.  Pl@ntNet is on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
Changed line 7 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH).
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works on content-based image retrieval (e.g. A posteriori multi-probe and RMMH). ([[http://m.plantnet-project.org/ | Try the web version !]])
February 10, 2016, at 10:07 AM by 193.49.108.68 -
Changed lines 4-5 from:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-ends has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. [[http://m.plantnet-project.org/ | Try the web version !]]
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity ([[http://m.plantnet-project.org/ | Try the web version !]]).  Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]].
Changed line 7 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH).
February 10, 2016, at 09:02 AM by 193.49.108.68 -
Changed line 4 from:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-ends has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. [[http://m.plantnet-project.org/ | Try it !]]
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-ends has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. [[http://m.plantnet-project.org/ | Try the web version !]]
February 10, 2016, at 09:02 AM by 193.49.108.68 -
Changed line 4 from:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. [[http://m.plantnet-project.org/ | Try it !]]
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-ends has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. [[http://m.plantnet-project.org/ | Try it !]]
February 10, 2016, at 09:01 AM by 193.49.108.68 -
Changed line 4 from:
[[http://www.plantnet-project.org/|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.
to:
[[http://www.plantnet-project.org/papyrus.php?langue=en|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. [[http://m.plantnet-project.org/ | Try it !]]
February 09, 2016, at 06:12 PM by 128.93.176.76 -
February 09, 2016, at 06:08 PM by 128.93.176.76 -
February 09, 2016, at 05:18 PM by 128.93.176.76 -
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* '''SnoopIm: Geometrically Consistent Retrieval and Mining of Visual Entities'''  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is currently being integrated in the [[http://www.cetanet.org/|CetaNet]] web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
to:
* '''SnoopIm: Geometrically Consistent Retrieval and Mining of Visual Entities'''  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is currently being integrated in the [[http://www.cetanet.org/|CetaNet]] web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis) as well as an experimental platform dedicated to Egyptian hieroglyphs.
February 09, 2016, at 05:17 PM by 128.93.176.76 -
Changed line 16 from:
* '''SnoopIm: Geometrically Consistent Retrieval and Mining of Visual Entities'''  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is currently being integrated in the [[www.cetanet.org/|CetaNet]] web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
to:
* '''SnoopIm: Geometrically Consistent Retrieval and Mining of Visual Entities'''  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is currently being integrated in the [[http://www.cetanet.org/|CetaNet]] web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
February 09, 2016, at 05:15 PM by 128.93.176.76 -
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* '''IKONA (INRIA CBIR engine)''' - IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of visual features. It offers a wide range of interactive search and navigation methods including query-by-example, query-by-window, relevance feedback or search results clustering. I have been actively participating to the conception and development of the core engine. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
to:
* '''IKONA (CBIR engine)''' - IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of visual features. It offers a wide range of interactive search and navigation methods including query-by-example, query-by-window, relevance feedback or search results clustering. I have been actively participating to the conception and development of the core engine. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
February 09, 2016, at 05:15 PM by 128.93.176.76 -
Changed line 16 from:
* '''SnoopIm''', Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is currently being integrated in the [[www.cetanet.org/|CetaNet]] web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
to:
* '''SnoopIm: Geometrically Consistent Retrieval and Mining of Visual Entities'''  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is currently being integrated in the [[www.cetanet.org/|CetaNet]] web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
February 09, 2016, at 05:14 PM by 128.93.176.76 -
Changed line 16 from:
* '''SnoopIm''', Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is integrated in the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
to:
* '''SnoopIm''', Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is currently being integrated in the [[www.cetanet.org/|CetaNet]] web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
February 09, 2016, at 05:12 PM by 128.93.176.76 -
Changed lines 16-21 from:
* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is integrated in the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).


* '''INA Video Copy Detection software''', used in [[http://www.institut-national-audiovisuel.fr/en/products-services/signature.html|INA SIGNATURE]] product by [[http://www.ina.fr/| INA]], one of the world leader in digital archiving. This system continuously monitors hundreds of TV channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (with more than 100,000 hours of archives). The technology is used by several major French actors in the TV, film and web industry (TF1, Canal+, M6, Dailymotion, TDF, EuropaCorp). My contribution concerns the development of the core content-based video retrieval technology.

* '''IKONA (INRIA CBIR engine)''', IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of visual features. It offers a wide range of interactive search and navigation methods including query-by-example, query-by-window, relevance feedback or search results clustering. I have been actively participating to the conception and development of the core engine. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
to:
* '''SnoopIm''', Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]]  web application (developed by INA) and it is integrated in the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).


* '''INA Video Copy Detection software''' - used in [[http://www.institut-national-audiovisuel.fr/en/products-services/signature.html|INA SIGNATURE]] product by [[http://www.ina.fr/| INA]], one of the world leader in digital archiving. This system continuously monitors hundreds of TV channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (with more than 100,000 hours of archives). The technology is used by several major French actors in the TV, film and web industry (TF1, Canal+, M6, Dailymotion, TDF, EuropaCorp). My contribution concerns the development of the core content-based video retrieval technology.

* '''IKONA (INRIA CBIR engine)''' - IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of visual features. It offers a wide range of interactive search and navigation methods including query-by-example, query-by-window, relevance feedback or search results clustering. I have been actively participating to the conception and development of the core engine. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
February 09, 2016, at 05:11 PM by 128.93.176.76 -
Changed lines 14-16 from:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage, besides scalability, is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm and IKONA softwares.

* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the DigInPix web application (developed by INA) and it is integrated in the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
to:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage, besides scalability, is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the [[http://diginpix.ina.fr/|DigInPix]] web application (developed by INA). It is integrated in the SnoopIm and IKONA softwares.

* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the [[http://diginpix.ina.fr/|DigInPix]] web application (developed by INA) and it is integrated in the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
February 09, 2016, at 05:10 PM by 128.93.176.76 -
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* '''IKONA (INRIA CBIR engine)''', IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of visual features. It offers a wide range of interactive search and navigation methods including query-by-example, query-by-window, relevance feedback or search results clustering. I have been participating to the development of the core engine. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
to:
* '''IKONA (INRIA CBIR engine)''', IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of visual features. It offers a wide range of interactive search and navigation methods including query-by-example, query-by-window, relevance feedback or search results clustering. I have been actively participating to the conception and development of the core engine. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
February 09, 2016, at 05:09 PM by 128.93.176.76 -
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* '''IKONA (INRIA CBIR engine)''', IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module). It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
to:
* '''IKONA (INRIA CBIR engine)''', IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of visual features. It offers a wide range of interactive search and navigation methods including query-by-example, query-by-window, relevance feedback or search results clustering. I have been participating to the development of the core engine. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
February 09, 2016, at 05:08 PM by 128.93.176.76 -
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* '''IKONA (INRIA CBIR engine)''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]). IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
to:
* '''IKONA (INRIA CBIR engine)''', IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module). It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application.
February 09, 2016, at 05:07 PM by 128.93.176.76 -
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* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
to:
* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  It is currently the core technology of the DigInPix web application (developed by INA) and it is integrated in the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
February 09, 2016, at 05:05 PM by 128.93.176.76 -
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* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities (conception=50%, development=30%)  - it integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
to:
* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities  - integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
February 09, 2016, at 05:05 PM by 128.93.176.76 -
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* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage, besides scalability, is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software.
to:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage, besides scalability, is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm and IKONA softwares.
February 09, 2016, at 05:03 PM by 128.93.176.76 -
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* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software.
to:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage, besides scalability, is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software.
February 09, 2016, at 05:03 PM by 128.93.176.76 -
Changed lines 14-16 from:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software.\\

* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities (conception=50%, development=30%)  - it integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis)\\
to:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software.

* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities (conception=50%, development=30%)  - it integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis).
February 09, 2016, at 05:02 PM by 128.93.176.76 -
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* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software. \\
to:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software.\\
February 09, 2016, at 05:02 PM by 128.93.176.76 -
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Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.
to:
[[http://www.plantnet-project.org/|Pl@ntNet]] is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.
Changed lines 13-16 from:
The two following softwares are currently running on the server side of the Pl@ntNet mobile applications, as well as in the DigInPix web application (developed by INA), and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis):

* '''PMH: Probabilistic Multi-probe Hashing library'''
- integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage over the concurrent softwares (e.g. FLANN) is its genericity in terms of query types, metrics and data formats.\\
* ""SnoopIm"": Geometrically consistent retrieval and mining
of visual entities (conception=50%, development=30%)  - it integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).\\
to:

* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search,
as well as other methods of the state-of-the-art. One of its main advantage is its genericity in terms of query types, metrics and data formats. It is currently running on the server side of the [[http://www.plantnet-project.org/|Pl@ntNet]] application, as well as in the DigInPix web application (developed by INA). It is integrated in the SnoopIm software. \\
* '''SnoopIm''': Geometrically consistent retrieval and mining of visual entities
(conception=50%, development=30%)  - it integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).  and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis)\\
February 09, 2016, at 04:58 PM by 128.93.176.76 -
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* ""PMH: Probabilistic Multi-probe Hashing library"" - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage over the concurrent softwares (e.g. FLANN) is its genericity in terms of query types, metrics and data formats.\\
to:
* '''PMH: Probabilistic Multi-probe Hashing library''' - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage over the concurrent softwares (e.g. FLANN) is its genericity in terms of query types, metrics and data formats.\\
February 09, 2016, at 04:57 PM by 128.93.176.76 -
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]
February 09, 2016, at 04:56 PM by 128.93.176.76 -
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! Pl@ntNet platform and Apps
to:
! Pl@ntNet Platform and Apps
Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.

Deleted line 9:
Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.
February 09, 2016, at 04:55 PM by 128.93.176.76 -
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  
Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.
||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
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to:
Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.
February 09, 2016, at 04:55 PM by 128.93.176.76 -
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Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.

 ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
to:
Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity. ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
February 09, 2016, at 04:55 PM by 128.93.176.76 -
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! Apps
to:
! Pl@ntNet platform and Apps
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] 
Pl@ntNet is a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.

 ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
Changed line 12 from:
Pl@ntNet: a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.
to:
February 09, 2016, at 04:52 PM by 128.93.176.76 -
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* '''INA Video Copy Detection software''', used in [[http://www.ina.fr/| INA]] industrial product [[http://www.institut-national-audiovisuel.fr/en/products-services/signature.html|INA SIGNATURE]] (one of the world leader in digital archiving). This system continuously monitors more hundreds of TV channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (with more than 100,000 hours of archives). My contribution concerns the development of the core content-based video retrieval technology.
to:
* '''INA Video Copy Detection software''', used in [[http://www.institut-national-audiovisuel.fr/en/products-services/signature.html|INA SIGNATURE]] product by [[http://www.ina.fr/| INA]], one of the world leader in digital archiving. This system continuously monitors hundreds of TV channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (with more than 100,000 hours of archives). The technology is used by several major French actors in the TV, film and web industry (TF1, Canal+, M6, Dailymotion, TDF, EuropaCorp). My contribution concerns the development of the core content-based video retrieval technology.
February 09, 2016, at 04:50 PM by 128.93.176.76 -
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* '''INA Video Copy Detection software''', used in [[http://www.ina.fr/| INA]] industrial system [[http://www.institut-national-audiovisuel.fr/en/products-services/signature.html|INA SIGNATURE]]. This system continuously monitors more than 30 channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (up to 100,000 hours of archives). My contribution concerns the development of several libraries dedicated to large scale content-based video copy detection:
** Fast interest points detectors
** Video local signatures extraction
** Distortion-based large scale similarity search
** Spatio-temporal registration of local results
to:
* '''INA Video Copy Detection software''', used in [[http://www.ina.fr/| INA]] industrial product [[http://www.institut-national-audiovisuel.fr/en/products-services/signature.html|INA SIGNATURE]] (one of the world leader in digital archiving). This system continuously monitors more hundreds of TV channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (with more than 100,000 hours of archives). My contribution concerns the development of the core content-based video retrieval technology.
February 09, 2016, at 04:48 PM by 128.93.176.76 -
Added lines 9-11:
Pl@ntNet: a participatory platform and information system dedicated to the production of botanical data through image-based plant identification. As the research supervisor of the platform, I did play a central role in the conception of the data models, system architecture and softwares. The mobile front-end has been downloaded by more than 1M persons in 170 countries, which makes it the Inria software with the largest audience. It generates each year millions of (noisy) plant observations that begin to be studied by researchers in ecology and (agro-)biodiversity.

Added lines 13-18:
The two following softwares are currently running on the server side of the Pl@ntNet mobile applications, as well as in the DigInPix web application (developed by INA), and the CetaNet web platform (aimed at monitoring whales in the context of a collaboration with two NGO’s: CetaMada and Globis):

* ""PMH: Probabilistic Multi-probe Hashing library"" - integrates most of my research works on hashing and approximate k-nn search, as well as other methods of the state-of-the-art. One of its main advantage over the concurrent softwares (e.g. FLANN) is its genericity in terms of query types, metrics and data formats.\\
* ""SnoopIm"": Geometrically consistent retrieval and mining of visual entities (conception=50%, development=30%)  - it integrates most of my works on visual objects retrieval as well as the work of two of my PhD students (Pierre Letessier and Valentin Leveau).\\

February 09, 2016, at 03:14 PM by 128.93.176.66 -
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(:notitle:)
April 10, 2014, at 09:30 AM by 193.49.107.147 -
Changed lines 4-6 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]

to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].
Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]

April 10, 2014, at 09:30 AM by 193.49.107.147 -
Changed lines 4-7 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]].  
Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]

to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]

April 10, 2014, at 09:30 AM by 193.49.107.147 -
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''[[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|Plantnet iphone app]]''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|iphone]] and [[https://play.google.com/store/apps/details?id=org.plantnet&hl=en|android]] app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
July 25, 2013, at 09:51 AM by 193.49.107.56 -
Changed lines 5-7 from:
Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH).

to:
Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH). Pl@ntNet is now on [[https://www.facebook.com/pages/Plantnet/488732104545546|Facebook]] and [[https://twitter.com/PlantNetProject|Twitter]]

July 25, 2013, at 09:50 AM by 193.49.107.56 -
Deleted lines 7-12:
! Patents
* [[http://v3.espacenet.com/textdoc?DB=EPODOC&IDX=US2006083429&F=0|'''US patent US2006083429''']], "Search of similar features representing objects in a large reference", A. Joly, patent deposited by INA, April 2006.

* [[http://v3.espacenet.com/textdoc?DB=EPODOC&IDX=US2006083429&F=0&RPN=EP1650683&DOC=cca34af198500dc9803dfcb67e36ddad54&QPN=EP1650683|'''European patent EP1650683''']], "Search of similar features representing objects in a large reference", A. Joly, patent deposited by INA, April 2006.

Deleted lines 8-9:
* '''IKONA (INRIA CBIR engine)''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]). IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
Changed lines 10-14 from:
** Fast interest points detectors, C, about 3000 lines of code
** Video local signatures extraction, C++ and C, about 2000 lines of code
** Distortion-based large scale similarity search, C++, about 6000 lines of code
** Spatio
-temporal registration of local results, C++, about 2000 lines of code
** Tests and Optimization, C++, about 4000 lines
of code
to:
** Fast interest points detectors
** Video local signatures extraction
** Distortion-based large scale similarity search
** Spatio-temporal registration of local results

* '''IKONA (INRIA CBIR engine)''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]). IKONA is a generalist software dedicated to content
-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).


! Patents
* [[http://v3.espacenet.com/textdoc?DB=EPODOC&IDX=US2006083429&F=0|'''US patent US2006083429''']], "Search of similar features representing objects in a large reference", A. Joly, patent deposited by INA, April 2006.

* [[http://v3.espacenet.com/textdoc?DB=EPODOC&IDX=US2006083429&F=0&RPN=EP1650683&DOC=cca34af198500dc9803dfcb67e36ddad54&QPN=EP1650683|'''European patent EP1650683''']], "Search of similar features representing objects in a large reference", A. Joly, patent deposited by INA, April 2006.
July 25, 2013, at 09:46 AM by 193.49.107.56 -
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''[[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|Plantnet iphone app]]''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
July 23, 2013, at 04:07 PM by 128.93.176.4 -
Changed line 17 from:
* '''INA Video Copy Detection software''', used in [[http://www.ina.fr/| INA]] industrial system [[http://www.ina.fr/entreprise/activites/recherche-audiovisuelle/signature.html|INA SIGNATURE]]. This system continuously monitors more than 30 channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (up to 100,000 hours of archives). My contribution concerns the development of several libraries dedicated to large scale content-based video copy detection:
to:
* '''INA Video Copy Detection software''', used in [[http://www.ina.fr/| INA]] industrial system [[http://www.institut-national-audiovisuel.fr/en/products-services/signature.html|INA SIGNATURE]]. This system continuously monitors more than 30 channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (up to 100,000 hours of archives). My contribution concerns the development of several libraries dedicated to large scale content-based video copy detection:
February 28, 2013, at 10:56 AM by 128.93.176.66 -
Changed lines 5-7 from:
Among other features, this free app helps identifying plant species from photographs, through a visual recognition software using several of my research results (Large-scale matching, A posteriori multi-probe, RMMH).

to:
Among other features, this free app helps identifying plant species from photographs, through a visual search engine using several of my works (Large-scale matching, A posteriori multi-probe, RMMH).

February 28, 2013, at 10:55 AM by 128.93.176.66 -
Changed line 4 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD), with the participation of the [[http://www.tela-botanica.org/|Tela Botanica]] social network, and the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD) and the members of [[http://www.tela-botanica.org/|Tela Botanica]] social network with the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
February 28, 2013, at 10:54 AM by 128.93.176.66 -
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[http://www.tela-botanica.org/|Tela Botanica]] social network, and the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, IRD), with the participation of the [[http://www.tela-botanica.org/|Tela Botanica]] social network, and the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
February 28, 2013, at 10:54 AM by 128.93.176.66 -
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||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[http://www.tela-botanica.org/||Tela Botanica]] social network, and the financial support of [[http://www.agropolis.fr/||Agropolis fondation]]. 
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/|Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[http://www.tela-botanica.org/|Tela Botanica]] social network, and the financial support of [[http://www.agropolis.fr/|Agropolis fondation]]. 
February 28, 2013, at 10:53 AM by 128.93.176.66 -
Changed line 4 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ http://www.tela-botanica.org/||Tela Botanica]] social network, and the financial support of [[ http://www.agropolis.fr/ ||Agropolis fondation]]. 
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[http://www.tela-botanica.org/||Tela Botanica]] social network, and the financial support of [[http://www.agropolis.fr/||Agropolis fondation]]. 
February 28, 2013, at 10:53 AM by 128.93.176.66 -
Changed line 4 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ ||Tela Botanica]] social network, and the financial support of [[ ||Agropolis fondation]]. 
to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ http://www.tela-botanica.org/||Tela Botanica]] social network, and the financial support of [[ http://www.agropolis.fr/ ||Agropolis fondation]]. 
February 28, 2013, at 10:52 AM by 128.93.176.66 -
Changed lines 4-6 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ ||Tela Botanica]] social network, and the financial support of [[ ||Agropolis fondation]].  Among other features, this free app helps identifying plant species from photographs, through a visual recognition software using several of my research results (Large-scale matching, A posteriori multi-probe, RMMH).

to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ ||Tela Botanica]] social network, and the financial support of [[ ||Agropolis fondation]]. 
Among other features, this free app helps identifying plant species from photographs, through a visual recognition software using several of my research results (Large-scale matching, A posteriori multi-probe, RMMH).

February 28, 2013, at 10:51 AM by 128.93.176.66 -
Changed lines 4-6 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] ||  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ ||Tela Botanica]] social network, and the financial support of [[ ||Agropolis fondation]].  Among other features, this free app helps identifying plant species from photographs, through a visual recognition software using several of my research results (Large-scale matching, A posteriori multi-probe, RMMH).

to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ ||Tela Botanica]] social network, and the financial support of [[ ||Agropolis fondation]].  Among other features, this free app helps identifying plant species from photographs, through a visual recognition software using several of my research results (Large-scale matching, A posteriori multi-probe, RMMH).

February 28, 2013, at 10:51 AM by 128.93.176.66 -
Changed lines 4-12 from:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] ||  ||'''Pl@ntNet iphone app''': Pl@ntNet is an image sharing and retrieval application for the identification of plants.

It is developed by scientists from four French research organisations (Cirad, INRA, Inria and IRD), and the Tela Botanica network, with the financial support of Agropolis fondation.

Among other features, this free app helps identifying plant species from photographs, through a visual recognition software.

Plant species that are well enough illustrated in the botanical reference database can be easily recognized
.

to:
||%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] ||  ||'''Plantnet iphone app''': an image sharing and retrieval application for the identification of plants. It is developed in the context of the [[http://www.plantnet-project.org/||Pl@ntNet]] project by scientists from four French research organisations (INRIA, Cirad, INRA, and IRD), with the participation of the [[ ||Tela Botanica]] social network, and the financial support of [[ ||Agropolis fondation]].  Among other features, this free app helps identifying plant species from photographs, through a visual recognition software using several of my research results (Large-scale matching, A posteriori multi-probe, RMMH).

February 28, 2013, at 10:43 AM by 128.93.176.66 -
Changed lines 3-5 from:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] || '''Pl@ntNet iphone app'''
Pl@ntNet is an image sharing and retrieval application for the identification of plants.
to:
|| border=0
||
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] ||  ||'''Pl@ntNet iphone app''': Pl@ntNet is an image sharing and retrieval application for the identification of plants.
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February 28, 2013, at 10:42 AM by 128.93.176.66 -
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%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] '''Pl@ntNet iphone app'''
to:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] || '''Pl@ntNet iphone app'''
February 28, 2013, at 10:41 AM by 128.93.176.66 -
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%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] !! ''Pl@ntNet iphone app''
to:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] '''Pl@ntNet iphone app'''
February 28, 2013, at 10:41 AM by 128.93.176.66 -
Changed lines 3-4 from:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] !! Pl@ntNet Iphone app (from Pl@ntNet project)
to:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] !! ''Pl@ntNet iphone app''
Pl@ntNet is an image sharing and retrieval application for the identification of plants.

It is developed by scientists from four French research organisations (Cirad, INRA, Inria and IRD
), and the Tela Botanica network, with the financial support of Agropolis fondation.

Among other features, this free app helps identifying plant species from photographs, through a visual recognition software.

Plant species that are well enough illustrated in the botanical reference database can be easily recognized.

February 28, 2013, at 10:40 AM by 128.93.176.66 -
Changed lines 3-4 from:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] !! PlantNet Iphone app (from Pl@ntNet project)
to:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] !! Pl@ntNet Iphone app (from Pl@ntNet project)
February 28, 2013, at 10:39 AM by 128.93.176.66 -
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%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]
to:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]] !! PlantNet Iphone app (from Pl@ntNet project)
February 28, 2013, at 10:38 AM by 128.93.176.66 -
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%width=170% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]
to:
%width=120% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]
February 28, 2013, at 10:38 AM by 128.93.176.66 -
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[[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]
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%width=170% [[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]
February 28, 2013, at 10:37 AM by 128.93.176.66 -
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[[https://itunes.apple.com/fr/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]
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[[https://itunes.apple.com/en/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]
February 28, 2013, at 10:35 AM by 128.93.176.66 -
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! Apps
[[https://itunes.apple.com/fr/app/plantnet/id600547573?mt=8|http://www-sop.inria.fr/members/Alexis.Joly/PlantNet.png]]

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** Tests and Optimization, C++, about 4000 lines of code
to:
** Tests and Optimization, C++, about 4000 lines of code
August 06, 2010, at 04:08 PM by 128.93.24.22 -
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* '''IKONA (INRIA CBIR engine)''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]), IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
to:
* '''IKONA (INRIA CBIR engine)''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]). IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
August 06, 2010, at 04:08 PM by 128.93.24.22 -
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* '''INRIA IKONA CBIR engine''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]), IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
to:
* '''IKONA (INRIA CBIR engine)''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]), IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
August 06, 2010, at 04:07 PM by 128.93.24.22 -
Changed lines 9-10 from:
* '''IKONA CBIR search engine''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]), IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
to:
* '''INRIA IKONA CBIR engine''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]), IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
August 06, 2010, at 04:07 PM by 128.93.24.22 -
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* '''INA TV monitoring Tools''', used in [[http://www.ina.fr/| INA]] industrial system [[http://www.ina.fr/entreprise/activites/recherche-audiovisuelle/signature.html|INA SIGNATURE]]). Allows the continuous monitoring of about 30 channels in order to detect automatically the broadcast of video sequences belonging to a large reference catalog (up to 50,000 hours of archives).
** Fast Harris interest points detector,
C, about 3000 lines of code
to:
* '''INA Video Copy Detection software''', used in [[http://www.ina.fr/| INA]] industrial system [[http://www.ina.fr/entreprise/activites/recherche-audiovisuelle/signature.html|INA SIGNATURE]]. This system continuously monitors more than 30 channels in order to automatically detect the broadcast of video sequences belonging to a large reference catalog (up to 100,000 hours of archives). My contribution concerns the development of several libraries dedicated to large scale content-based video copy detection:
** Fast interest points detectors
, C, about 3000 lines of code
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** Distortion-based similarity search, C++, about 6000 lines of code
to:
** Distortion-based large scale similarity search, C++, about 6000 lines of code
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* '''Pss-struct''', Probabilistic similarity search package, C++ and C, about 5000 lines of code. Allows the fast similarity search of multidimensional features in very large databases.
August 06, 2010, at 04:03 PM by 128.93.24.22 -
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* '''TV monitoring Tools''', used in [[http://www.ina.fr/| INA]] industrial system (more details [[http://www.ina.fr/entreprise/activites/recherche-audiovisuelle/signature.html|here]]). Allows the continuous monitoring of about 10 channels in order to detect automatically the broadcast of video sequences belonging to a large reference catalog (up to 50,000 hours of archives).
to:
* '''INA TV monitoring Tools''', used in [[http://www.ina.fr/| INA]] industrial system [[http://www.ina.fr/entreprise/activites/recherche-audiovisuelle/signature.html|INA SIGNATURE]]). Allows the continuous monitoring of about 30 channels in order to detect automatically the broadcast of video sequences belonging to a large reference catalog (up to 50,000 hours of archives).
August 06, 2010, at 04:01 PM by 128.93.24.22 -
Changed lines 9-10 from:
* '''IKONA CBIR search engine''' (more details [[http://www-c.inria.fr/Internet/partnerships/industrial-relations/softwares/ikona|here]]), participation to the development of the core engine and development of several complete packages including an indexing structures package and a local visual features package
to:
* '''IKONA CBIR search engine''' (more details [[http://www.inria.fr/rocquencourt/partnerships/industrial-relations/softwares/ikona|here]]), IKONA is a generalist software dedicated to content-based visual information indexing and retrieval. Its main functionalities are the extraction, the management and the indexing of many state-of-the-art global and local visual features. It offers a wide range of interactive search and navigation methods  including query-by-example, query-by-window, matching, relevance feedback, search results clustering or automatic annotation. It can manage several types of input data including images, videos and 3D models. Based on a client/server architecture, it is easily deployable in any multimedia search engine or service. I have been participating to the development of the core engine and I fully developed two packages for the extraction of local visual features and for large scale similarity search (multidimensional indexing structures module).
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%rfloat% http://www-rocq.inria.fr/~ajoly/keyboard.jpeg
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* '''IKONA CBIR search engine''' (more details [[http://www-c.inria.fr/Internet/partnerships/industrial-relations/softwares/ikona|here]]), participation to the development of several modules including an indexing structures package, a local visual features
to:
* '''IKONA CBIR search engine''' (more details [[http://www-c.inria.fr/Internet/partnerships/industrial-relations/softwares/ikona|here]]), participation to the development of the core engine and development of several complete packages including an indexing structures package and a local visual features package
Added lines 8-9:
* '''IKONA CBIR search engine''' (more details [[http://www-c.inria.fr/Internet/partnerships/industrial-relations/softwares/ikona|here]]), participation to the development of several modules including an indexing structures package, a local visual features
Changed line 8 from:
* '''TV monitoring Tools''', used in [[http://www.ina.fr/| INA]] industrial system (more details [[Main.MyPhdResearchActivitiesAtINA#INAsyst|here]]). Allows the continuous monitoring of about 10 channels in order to detect automatically the broadcast of video sequences belonging to a large reference catalog (up to 50,000 hours of archives).
to:
* '''TV monitoring Tools''', used in [[http://www.ina.fr/| INA]] industrial system (more details [[http://www.ina.fr/entreprise/activites/recherche-audiovisuelle/signature.html|here]]). Allows the continuous monitoring of about 10 channels in order to detect automatically the broadcast of video sequences belonging to a large reference catalog (up to 50,000 hours of archives).

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